Re-thinking Housing and Mobility – A European Living Lab for Sustainable Mobility in Munich
Bibliographic record
Abstract
This paper aims to describe the vision and implementation approach of a sustainable and innovative mobility \nand housing concept of a city district at the pericentral edge of Munich. Within the European CIVITAS \ninitiative, the ECCENTRIC project demonstrates an innovative approach to mobilize residents by offering \nintermodal mobility and mobility on demand. With around 8000 new inhabitants and 12,000 new employees \nwithin the next years, the transport system in the Munich living lab Domagkpark and Parkstadt Schwabing \nneeds an integrative and innovative approach to ensure a functioning, ecologically compatible and socially \nacceptable mobility supply. Central objective is to increase quality of life in the district through a substantial \nroll-out of innovative mobility solutions, that reduce the use (and number) of private cars.With the \nimplementation of various project measures in the field of sustainable and shared mobility, mobility \nmanagement, city logistics and road security, a new model quarter for sustainable urban development and \ncompatible mobility will be development. Successful research findings aim to be implemented in future \nnewly-built quarters of Munich and replicated in other European cities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".